Triple
T9716369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungerford massacre |
E235152
|
entity |
| Predicate | perpetratorKilledFamilyMember |
P45023
|
FINISHED |
| Object | mother |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: mother | Statement: [Hungerford massacre, perpetratorKilledFamilyMember, mother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: perpetratorKilledFamilyMember Context triple: [Hungerford massacre, perpetratorKilledFamilyMember, mother]
-
A.
killedFamilyOf
chosen
Indicates that one entity caused the death of one or more members of another entity’s family.
-
B.
perpetratorOfKilling
Indicates that an entity is the one who carried out or caused a particular killing.
-
C.
perpetratorDeath
Indicates that the referenced individual is the one who caused or is responsible for another entity’s death.
-
D.
numberOfPerpetratorsKilled
Indicates the count of perpetrators who were killed in the context of the described event or incident.
-
E.
numberOfChildrenMurdered
Indicates the count of children who have been killed in an act of murder.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca84cd8fa0819090a5e243ceb37003 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e0bb82081908e21a646f4de1a61 |
completed | April 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69cd03bfeca08190924fca43aaa9c10f |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:20 p.m.